Wealth Inequality in the United States since 1913: Evidence from Capitalized Income Tax Data

Abstract

This paper combines income tax returns with Flow of Funds data to estimate the distribution of household wealth in the United States since 1913. We estimate wealth by capitalizing the incomes reported by individual taxpayers, accounting for assets that do not generate taxable income. We successfully test our capitalization method in three micro datasets where we can observe both income and wealth: the Survey of Consumer Finance, linked estate and income tax returns, and foundations' tax records. Wealth concentration has followed a U-shaped evolution over the last 100 years: It was high in the beginning of the twentieth century, fell from 1929 to 1978, and has continuously increased since then. The rise of wealth inequality is almost entirely due to the rise of the top 0.1% wealth share, from 7% in 1979 to 22% in 2012-a level almost as high as in 1929. The bottom 90% wealth share first increased up to the mid-1980s and then steadily declined. The increase in wealth concentration is due to the surge of top incomes combined with an increase in saving rate inequality. Top wealth-holders are younger today than in the 1960s and earn a higher fraction of total labor income in the economy. We explain how our findings can be reconciled with Survey of Consumer Finances and estate tax data.

When does inequality freeze an economy?

“…The subject has regained much interest recently, in view of the claim that levels of inequality have reached the same levels as in the beginning of the 20th century [11]. Saez and Zucman [13] corroborate these findings, studying the evolution of the distribution of wealth in the US economy over the last century, and they find an increasing concentration of wealth in the hands of the 0.01% of the richest. Figure 1 shows that the data in Saez and Zucman [13] is consistent with a power law distribution P {w i > x} ∼ x −β , with a good agreement down to the 10% of the richest (see caption 1 ).…”

“…Much research has focused The data on the money velocity is retrieved from [5], the data on the wealth distribution is taken from [13]. Inset: relation between the fraction w > of wealth owned by the P > percent wealthiest individuals, and P > for the years 1980, 1990, 2000 and 2010 (see footnote 1).…”

Genes and Gini: What Inequality Means for Heritability

“…In the US, the change in inequality has followed a U-shaped trajectory over the last 100 years: high in the beginning of the 20th century, falling between 1929 and the late 1970s, and continuously increasing since then (e.g. 0.40 in 1976 and 0.47 in 2006), with the 2012 Gini being almost as high as in 1929 (Piketty & Saez, 2003;Saez & Zucman, 2014;Sommeiller & Price, 2015;Atkinson et al, 2011).…”

“…In the US, between 2009 and 2012, all income growth happened in the top 1% of earners in eighteen of the states; and in New York and Connecticut, the top 1% of earners attained average incomes more than 48 times that of the bottom 99% (Sommeiller & Price, 2015). Over 1989 and 2013 the top 10% owned 87.7% of household wealth, the top 1% owned 50.8% and the top 0.1% had 20.3% (Saez & Zucman, 2014). These trends have happened against a background of increases in absolute wealth, with per capita PPP increasing from US$37,062 in 1990 to US$52,549 in 2015(UNDP, 2016, with the US remaining the richest region in the world (Allianz, 2016).…”

Dynamic Status Effects, Savings, and Income Inequality

“…However, empirical evidence indicates that saving rates are higher for richer countries (Loayza, Schmidt-Hebbel, and Serven, 2000). Also, examining historical data for the US, Saez and Zucman (2016) find that the saving rates tend to rise with wealth. Furthermore, Weil (2005) documents that the saving rate amounts to about 5 percent on average for countries in the lowest income decile 6 (i.e.…”